new b.e. semester vii · 2019. 12. 30. · term work (25) total theory tutorial practical contact...

B.E. Semester –VII

B.E. ( Computer Engineering ) B.E. SEM : VII

Course Name : Digital Signal & Image Processing Course Code :CSC701

Teaching Scheme (Program Specific) Examination Scheme (Formative/ Summative)

Modes of Teaching / Learning / Weightage Modes of Continuous Assessment / Evaluation

Hours Per Week Theory

(100)

Practical/Oral

(25)

Term

Work (25)

Total

Theory Tutorial Practical Contact

Hours

Credits IA ESE PR/OR TW

125 4 - 2 6 5 20 80 -

25

IA: In-Semester Assessment - Paper Duration – 1 Hours

ESE: End Semester Examination - Paper Duration - 3 Hours

The weightage of marks for continuous evaluation of Term work/Report: Formative (40%), Timely

completion of practical (40%) and Attendance/Learning Attitude (20%)

Prerequisite: Engineering Mathematics,Basic Knowledge of Signals and System

Course Objective:Thecourse intends to deliver the concepts of digital signal processing and Image

processing and apply this knowledge on different image processing aspects.

Course Outcomes:Upon completion of the course students will be able to:

Sr.

No.

Course Outcomes Cognitive levels of

attainment as per

Bloom’s Taxonomy

1 Apply the concept of DT Signal and DT Systems. L1, L2, L3

2 Classify and analyze discrete time signals and systems. L1, L2, L3, L4

3 Experiment with Digital Signal Transform techniques DFT and FFT. L1, L2, L3,L4 4 Make use of enhancement techniques for digital Image Processing. L1, L2

5 Explain advantages and disadvantages of different edge detection

techniques.

L1, L2, L3

6 Develop small projects of 1-D and 2-D Digital Signal Processing. L1, L2, L3

Detailed Syllabus:

Module

No.

Topics Hrs. Cognitive levels

of attainment as

per Bloom’s

Taxonomy

1 Discrete-Time Signal and Discrete-Time System

12

L1, L2, L3 Introduction to Digital Signal Processing, Sampling and Reconstruction,

Standard DT Signals, Concept of Digital Frequency, Representation of

DT signal using Standard DT Signals, Signal Manipulations(shifting,

reversal, scaling, addition, multiplication).

Classification of Discrete-Time Signals, Classification of Discrete-

Systems

Linear Convolution formulation for 1-D and 2-D signal (without

mathematical proof), Circular Convolution (without mathematical

proof), Linear convolution using Circular Convolution. Auto andCross

Correlation formula evaluation, LTI system, Concept ofImpulse

Response and Step Response, Output of DT system usingTime Domain

Linear Convolution. 2 Discrete Fourier Transform

6

L1, L2, L3, L4 Introduction to DTFT, DFT, Relation between DFT and DTFT, IDFT

Properties of DFT without mathematical proof (Scaling and Linearity,

Periodicity, Time Shift and Frequency Shift, Time Reversal,

Convolution Property and Parsevals’ Energy Theorem). DFT

computation using DFT properties.

Transfer function of DT System in frequency domain using DFT.

Linear and Circular Convolution using DFT, Convolution of long

sequences, Introduction to 2-D DFT 3 Fast Fourier Transform

6

L1, L2, L3, L4

Need of FFT, Radix-2 DIT-FFT algorithm,

FFT Flow graph for N=4 and 8, Inverse FFT algorithm. Spectral Analysis using FFT

4 Digital Image Fundamentals 8 L1, L2

Introduction to Digital Image, Digital Image Processing System,

Sampling and Quantization

Representation of Digital Image, Connectivity

Image File Formats: BMP, TIFF and JPEG.

5 Image Enhancement in Spatial domain 12 L1, L2, L3

Gray Level Transformations, Zero Memory Point Operations,

Histogram Processing, Histogram equalization.

NeighborhoodProcessing, Spatial Filtering, Smoothing and Sharpening

Filters, Median Filter

6 Image Segmentation 8 L1, L2, L3

Segmentation based on Discontinuities (point, Line, Edge),

Image Edge detection using Robert, Sobel, Previtt masks, Image Edge

detection using Laplacian Mask

Total Hours 52

Books and References:

Sr.

No.

Title Authors Publisher Edition Year

1 Digital Signal Processing:

Principles, Algorithms, and

Applications

John G. Proakis, Dimitris and

G.Manolakis

Pearson

Education

Fourth

Edition

2007

2 Digital Signal Processing A. Anand Kumar PHI Learning

Pvt. Ltd.

Second

Edition

2013

3 Digital Image Processing Rafel C. Gonzalez and Richard

E. Woods

Pearson

Education ThirdEdition 2009

4 Digital Image Processing S. Sridhar Oxford

University

Press

Second

Edition

2012

Online References:

Sr.

No.

Website Name URL Modules

Covered

1 www.tutorialspoint.com https://www.tutorialspoint.com/digital_signal_processi

ng/

M1,M2,M3

2 www.gnits.ac.in https://www.gnits.ac.in/sites/default/files/ONLINERES

OURCES/ECE/dsp.pdf https://lecturenotes.in/subject/44/digital-signal-

processing-dsp

M1,M2,M3

3 https://lecturenotes.in https://lecturenotes.in/subject/89/digital-image-

processing-dip

M4,M5,M6

List of Practical/ Experiments:

Practical

Number

Type of Experiment Practical/ Experiment Topic

Hrs.

Cognitive levels of

attainment as per

Bloom’s Taxonomy

1

Basic Experiments

Illustrate a program to sample a

continuous time signal and convert it to

Discrete Time Signal.

2

L1, L2, L3

2

Design Experiments

Develop a function to find auto-

correlation operation.

2

L1, L2, L3

3 Develop a function to find cross-

correlation operation. 2

L1, L2, L3

4 Experiment with Discrete Fourier

transform

2

L1, L2, L3

5 Develop a program to perform Fast

Fourier Transform of N point signal.

2

L1, L2, L3

6 Make use of Image negative, Gray level

Slicing and Thresholding on to a given

image

2

L1, L2, L3

https://www.tutorialspoint.com/digital_signal_processing/

https://www.tutorialspoint.com/digital_signal_processing/

https://www.gnits.ac.in/sites/default/files/ONLINERESOURCES/ECE/dsp.pdf

https://www.gnits.ac.in/sites/default/files/ONLINERESOURCES/ECE/dsp.pdf

https://lecturenotes.in/subject/44/digital-signal-processing-dsp




https://lecturenotes.in/subject/89/digital-image-processing-dip

https://lecturenotes.in/subject/89/digital-image-processing-dip

7 Make use of Contrast Stretching,

Dynamic range compression & Bit plane

Slicing to a given image

2

L1, L2, L3

8 Make use of Histogram Processing 2 L1, L2, L3

9 Make use of Image smoothing/ Image

sharpening to a given image 2

L1, L2, L3

10 Implementation of Edge detection using

Sobel and Previtt masks 2

L1, L2, L3

11

Mini/Minor

Projects/ Seminar/

Case Studies

Case Study:

1. Speech signal Processing

2. Biomedical Digital Signal

Processing

3. Image Security

4. Study on image cryptographic

algorithms.

4

L1, L2, L3,L4

13 Research Paper Presentation

1. Presentation on latest topics

from technical papers in

Survey of Signal Processing

Algorithm and Image

Processing.

2 L1, L2, L3,L4

13 Mini Project:

1. Optical character recognition

2. Text Recognition in Images

3. Face recognition

4. Fingerprint recognition

5. Handwriting recognition

4 L1, L2, L3, L4, L5, L6

Total Hours 30



Course Name :Mobile Communication & Computing Course Code :CSC702




(100)

Practical/Oral

(25)

Term

Work (25)

Total


Hours

Credits

IA ESE PR/OR TW

150 4 - 2 6 5 20 80 25 25

IA: In-Semester Assessment - Paper Duration – 1 Hour



completion of practical (40%) and Attendance/Learning Attitude (20%).

Prerequisite: Computer Networks

Course Objective:Thecourse intends toimpart fundamental concepts related to mobile communication

and computing as well as provide a perspective on the converging area of wireless networking, mobility

management and introduce recent research topics.


Sr.

No.


attainment as per

Bloom’s Taxonomy

1 Illustrate basic concepts and principles in mobile communication &

computing, cellular architecture.

L1, L2

2 Demonstrate the components and functioning of mobile networking. L1, L2, L3, L4

3 Classify variety of security techniques in mobile network. L1, L2, L3, L4

4 Apply the concepts of WLAN for local as well as remote applications. L1, L2, L3

5 Applytheconcepts of mobility management L1, L2, L3

6 Demonstrate Long Term Evolution (LTE) architecture and its

interfaces.

L1, L2

Detailed Syllabus:

Module

No.

Topics Hrs. Cognitive levels of

attainment as per

Bloom’s Taxonomy

1 Introduction to Mobile Computing 06 L1, L2

Introduction to Mobile Computing, Telecommunication Generations,

Cellular systems,Electromagnetic Spectrum, Antenna, Signal Propagation,

Signal Characteristics, Multiplexing, Spread Spectrum:DSSS& FHSS

2 GSM Mobile services 08

L1, L2, L3, L4 GSM Mobile services, System Architecture, Radio interface,

Protocols , Localization and Calling, Handover, security(A3,A5 & A8),

GPRS system and protocol architecture UTRAN , UMTS core network ;

Improvements on Core Network

3 Mobile Networking 10

L1, L2, L3, L4

Mobile Networking: Medium Access Protocol, InternetProtocol and

Transport layer,

Medium Access Control:Motivation for specialized MAC, Introduction to

multipleAccess techniques (MACA)

Mobile IP: IP Packet Delivery, Agent Advertisement and Discovery,

Registration, TunnellingandEncapsulation, Reverse Tunnelling, Routing

(DSDV,DSR)

Mobile TCP :

Traditional TCP, Classical TCP Improvements like IndirectTCP, Snooping

TCP & Mobile TCP, Fast Retransmit/ FastRecovery,

Transmission/Timeout Freezing, SelectiveRetransmission 4 Wireless Local Area Networks 10 L1, L2, L3

Wireless Local Area Networks : Introduction, Infrastructureand Ad-

Hocnetwork

IEEE 802.11:System architecture, Protocol architecture,Physical layer,

Medium access control layer, MAC

management, 802.11a, 802.11b

Wi-Fi security : WEP ,WPA, Wireless LAN Threats,Securing Wireless

Networks, HiperLAN 1 &HiperLAN 2 Bluetooth: Introduction, User Scenario, Architecture, protocolstack

5 Mobility Management 7

L1, L2, L3 Mobility Management : Introduction, IP Mobility,Optimization, IPv6

Macro Mobility : MIPv6, FMIPv6,

Micro Mobility:CellularIP, HAWAII, HMIPv6

6 Long-Term Evolution (LTE) of 3GPP 11

L1, L2 Long-Term Evolution (LTE) of 3GPP : LTE SystemOverview,

Evolution from UMTS to LTE

LTE/SAE Requirements, SAE Architecture

EPS: Evolved Packet System, E-UTRAN, Voice over LTE(VoLTE),

Introduction to LTE-Advanced System Aspects, LTE Higher Protocol

Layers, LTE MAClayer, LTE PHY Layer,

Self-Organizing Network (SON-LTE),SON for HeterogeneousNetworks

(HetNet), Introduction to 5G

Total Hours 52


Sr.

No.


1 Mobile Communication JochenSchilller Pearson Education Second

Edition

2017

2 Wireless

Communications &

Networks

William Stallings Pearson education

Second

Edition 2009

3 Mobile Computing Raj Kamal Oxford University

Press-New Delhi

Third

Edition

2018

4 LTE Self-Organizing

Networks (SON):

Network Management

Automation for

Operational Efficiency

SeppoHamalainen,

Henning Sanneck,

CinziaSartori,

Wiley publications First

Edition

2011

5 An Introduction to

LTE: LTE, LTE-

Advanced, SAE and 4G

Mobile

Communications

Christopher Cox Wiley publications Second

Edition

2014

6 Mobility Protocols and

Handover

Optimization: Design,

Evaluation and

Application

Ashutosh Dutta,

Henning Schulzrinne

IEEE Press, Wiley

Publication

First

Edition

2015

7 Build your own

security lab

Michael Gregg Wiley India edition First

Edition

2012

8 Emerging Wireless

Technologies and the

Future Mobile Internet

DipankarRaychaudhuri,

Mario Gerla

Cambridge First

Edition

2011

9 Wireless

Communications

Andreas F.Molisch Wiley Publication Second

Edition

2010

Online References:

Sr.

No.


Covered

1 www.coursera.org/ https://www.coursera.org/learn/wireless-

communications

M4

2 nptel.ac.in https://nptel.ac.in/courses/106106147/ M1-M6

3 vlab.amrita.edu http://vlab.amrita.edu/index.php?sub=78&brch=256 M1, M3, M5


Practical

Number

Type of Experiment Practical/ Experiment Topic Hrs. Cognitive levels

of attainment

as per Bloom’s

Taxonomy

1

Basic Experiments

Outline cellular architecture with

emphasis on the process of clustering

and frequency reuse.

2

L1, L2, L3

2 Compare the GSM security algorithms

i.e. A3, A5, A8

2 L1, L2, L3

3

Design Experiments

Apply a Bluetooth network to transfer a

file from one device to another.

2

L1, L2, L3

4 Apply basic function of Code Division

Multiple Access (CDMA) to test the

orthogonalityof a code to be used for

CDMA operation.

2

L1, L2, L3

5 Apply basic function of Code Division

Multiple Access (CDMA) to test the

autocorrelation of a code to be used for

CDMA operation.

2

L1, L2, L3

6 Apply setup & configuration of Wireless

Access Point (AP) using NS3.

2

L1, L2, L3

7 Develop an application that writes data

to the SD card.

2

L1, L2, L3

8 Develop an application that uses GUI

components.

2 L1, L2, L3

9 Develop an application that draws basic

graphical primitives on the screen.

2 L1, L2, L3

10 Develop an application that makes use of

database.

2 L1, L2, L3

11 Develop an application that creates an

alert upon receiving a message.

2 L1, L2, L3

12 Develop mobile node discovery 2 L1, L2, L3

13

Mini/Minor

Projects/ Seminar/

Case Studies

Case Study

1. Describe Long Term Evolution

(LTE) architecture and its

interfaces.

2. Describe and compare

HiperLAN 1 &HiperLAN 2

3. Describe and compare Macro

Mobility and Micro Mobility

Mini Project: Compare number of

packet retransmissions required in both

RTS/CTS wireless networks

6

L1, L2, L3, L4,

L5

Total Hours 30



Course Name :Artificial Intelligence & Soft Computing CSC703




(100)

Practical/Oral

(25)

Term

Work (25)

Total


Hours

Credits

IA ESE PR/OR TW

150 4 - 2 6 5 20 80 25 25





Prerequisite: Discrete Mathematics, Analysis of Algorithms, Data Structure

Course Objective:Thecourse intends to deliver the basic knowledge and techniques of AI and SC and

apply various AI and SC algorithms to create AI based real world applications/systems.

Course Outcomes: Upon completion of the course students will be able to:

Sr.

No.


attainment as per

Bloom’s Taxonomy

1 Evaluate the various characteristics of Artificial Intelligence and Soft

Computing techniques.

L1, L2, L3, L4, L5

2 Evaluate problem solving methods for an agent to find a sequence of actions

to reach the goal state.

L1, L2, L3, L4, L5

3 Review the strength and weakness of AI approaches to knowledge

representation, reasoning and planning.

L1, L2, L3

4 Design fuzzy controller system for real world application. L1, L2, L3, L4, L5, L6

5 Apply supervised and unsupervised ANN for real world applications. L1, L2, L3

6 Apply Hybrid approach for expert system design. L1, L2, L3

Detailed Syllabus:

Module

No.

Topics Hrs. Cognitive

levels as per

blooms

Taxonomy

1 Introduction to Artificial Intelligence(AI) and Soft Computing

4

L1, L2, L3,

L4, L5 Introduction and Definition of Artificial Intelligence.

Intelligent Agents: Agents and Environments, Rationality, Nature of

Environment, Structure of Agent, types of Agent.

Soft Computing: Introduction of soft computing, soft computing vs. hard

computing, various types of soft computing techniques.

2 Problem Solving

10

L1, L2, L3,

L4, L5 Problem Solving Agent, Formulating Problems, Example Problems

Uninformed Search Methods: Depth Limited Search, Depth First Iterative

Deepening (DFID), Informed Search Method: A* Search

Optimization Problems: Hill climbing Search, Simulated annealing, Genetic

algorithm

3 Knowledge, Reasoning and Planning

10

L1, L2, L3 Knowledge based agents First order

logic: syntax and Semantic, Knowledge Engineering in FOL, Inference in FOL :

Unification, Forward Chaining, Backward Chaining and Resolution

Planning Agent, Types of Planning: Partial Order, Hierarchical Order,

Conditional Order

4 Fuzzy Logic

12

L1, L2, L3,

L4, L5, L6 Introduction to Fuzzy Set: Fuzzy set theory, Fuzzy set versus crisp set, Crisp

relation & fuzzy relations, membership functions

Fuzzy Logic: Fuzzy Logic basics, Fuzzy Rules and Fuzzy Reasoning

Fuzzy inference systems: Fuzzification of input variables, defuzzification and

fuzzy controllers

5 Artificial Neural Network

12

L1, L2, L3

Introduction – Fundamental concept– Basic Models of Artificial Neural Networks

– Important Terminologies of ANNs – McCulloch-Pitts Neuron Neural

Network Architecture: Perceptron, Single layer Feed Forward ANN, Multilayer

Feed Forward ANN, Activation functions, Supervised Learning: Delta learning

rule, Back Propagation algorithm. Un-Supervised

Learning algorithm: Self Organizing Maps

6 Expert System

4

L1, L2, L3

Hybrid Approach - Fuzzy Neural Systems

Expert system : Introduction, Characteristics, Architecture, Stages in the

development of expert system

Total Hours 52


Sr.

No.


1 Artificial Intelligence a

Modern Approach

Stuart J. Russell and Peter

Norvig

McGraw Hill Third

Edition

2009

2 Introduction to soft computing Samir Roy and

Chakraborty

Pearson

Edition

First Edition 2013

3 Principles of Soft Computing S.N.Sivanandam,

S.N.Deepa

Wiley

Publication

Second

Edition

2011

4 Neural Networks, Fuzzy Logic

and Genetic Algorithms

S.Rajasekaran and

G.A.VijayalakshmiPai

PHI Learning Second

Edition

2017

5 Artificial Intelligence and

Intelligent Systems

N. P. Padhy Oxford First Edition

2005

6 Artificial Intelligence Elaine Rich and Kevin

Knight

Tata

McGraw-Hill

Education

Pvt. Ltd.

Third

Edition

2008

7 Neural Networks A Classroom

Approach

Satish Kumar Tata

McGraw-Hill

Education

Pvt. Ltd.

Second

Edition

2012

8 Fuzzy Set Theory and its

Applications

Zimmermann H.S Kluwer

Academic

Publishers

Fourth

Edition

2001

9 Neural Network Design Hagan, Demuth, Beale CENGAGE

Learning,

India Edition

Second

Edition

2014

10 Neuro-Fuzzy and Soft

Computing

J.-S.R.Jang PHI Third Edition 2003

11 Introduction to Artificial

Neural Sytems

Jacek M. Zurada Jaico

Publishing

House

First Edition 1994

Online References:

Sr. No. Website Name URL Modules Covered

1 https://nptel.ac.in https://nptel.ac.in/courses/106105077/ M1-3

2 https://nptel.ac.in https://nptel.ac.in/courses/106105173/ M4-6

https://nptel.ac.in/

https://nptel.ac.in/courses/106105077/

https://nptel.ac.in/

https://nptel.ac.in/courses/106105173/


Sr.

No.

Type of Experiment Practical/ Experiment Topic Hrs. Cognitive

levels as per

blooms

Taxonomy

1

Basic Experiment

(a)Specifyproblem formulation for an AI problem.

(b) Specify PEAS description for an AI agent.

2

L1, L2, L3,

L4, L5

2

Solve a given problem using uninformed search

technique.

2

L1, L2, L3,

L4, L5

3 Design Experiments Solve a given problem using informed search technique.

2

L1, L2, L3,

L4, L5

4

Develop solution to optimization problem using Genetic

Algorithm.

2

L1, L2, L3,

L4, L5

5

Build knowledge base for Wumpus world problem. 2 L1, L2, L3

6 Solve a reasoning problem using unification. 2 L1, L2, L3

7 Apply concepts of Fuzzy to develop a Fuzzy Controller

system.

2 L1, L2, L3

8

Apply Mc-Culloch Pitts Model to solve a classification

problem.

2 L1, L2, L3

9 Advanced

Experiments

Solve given problem using Supervised Neural Network. 2 L1, L2, L3

10 Solve given problem using unsupervised Neural

Network.

2 L1, L2, L3

11

Case Studies

Investigate a Case study on Hybrid Systems 2 L1, L2, L3, L4

12 Investigate a Case study of a real life /Industry based

Application

2

L1, L2, L3, L4

13 Mini Projects 1. Game Development

2. Chatbot

3. Pattern Recognition

4. Prediction

5. Smart Apps

6. Fuzzy System

6 L1, L2, L3,

L4, L5, L6

Total Hours 30

B.E. Semester–VII


Course Name :Department Level Optional Course –

III(Advanced System Security and Digital Forensics)

Course Code :CSDLO7031




(100)

Practical/Oral

(25)

Term

Work (25)

Total


Hours


150 4 - 2 6 5 20 80 25 25




completion of practical (40%) and Attendance/Learning Attitude (20%).

Prerequisite: System Security

Course Objective:Thecourse intends to deliver advanced concepts about System Security to develop

security management and policies for reducing Cyber-Attacks. It will also help in understanding and explore

techniques used in Digital Forensics and analyze various software vulnerabilities, attacks and protection in

Web Applications& Wi-Fi Networks


Sr. No. Course Outcomes Cognitive levels of

attainment as per

Bloom’s

Taxonomy

1 Apply access control policies and control mechanisms to cyber-attacks L1, L2, L3

2 Identify malicious code and targeted malicious code L1, L2, L3

3 Analyze threats to web applications L1, L2, L3, L4

4 Understand the vulnerabilities of Wi-Fi networks and explore different

measures to secure wireless protocols, WLAN and VPN network

L1, L2, L3, L4

5 Asses ethical and legal issues associated with cyber-crimes and be able to

mitigate impact of crimes with suitable policies

L1, L2, L3, L4, L5

6 Make use of different forensic tools to acquire and duplicate data from

compromised systems and analyze the same

L1, L2, L3, L4

Detailed Syllabus:


Sr.

No.


1. Computer Security Principles and

Practice

William Stallings Pearson Education Sixth Edition 2011

2. Security in Computing Charles P. fleeger Pearson Education Fifth Edition 2015

3. Network Security and Cryptography Bernard Menezes Cengage Learning Second Edition 2014

4. Network Security Bible Eric Cole Wiley Second Edition 2009

Module

No.


levels as per

blooms

Taxonomy

1 Introduction & Access Control

7

L1, L2, L3

Cyber-attacks, Vulnerabilities, Defense Strategies and Techniques, Authentication

Methods and Protocols, Defense in Depth Strategies

Access Control Policies: DAC, MAC, Multi-level Security Models: Biba Model,

Bell La Padula Model, Single Sign on, Federated Identity Management

2 Program & OS Security

7

L1, L2, L3

Malicious and Non-Malicious programming errors, Targeted Malicious codes:

Salami Attack, Linearization Attack, Covert Channel, Control against Program

threats, Operating System Security: Memory and Address protection, File Protection

Mechanism, User Authentication

Linux and Windows: Vulnerabilities, File System Security

3 Web Application Security

10 L1, L2, L3,

L4 OWASP, Web Security Considerations, User Authentication and Session

Management, Cookies, SSL, HTTPS, SSH, Privacy on Web, Web Browser Attacks,

Account Harvesting, Web Bugs, Clickjacking, Cross-Site Request Forgery, Session

Hijacking and Management, Phishing and Pharming Techniques, Web Service

Security, OAuth 2.0

4 Wireless Security

9 L1, L2, L3,

L4 Wi-Fi Security, WEP, WPA, WPA-2, Mobile Device Security- Security Threats,

Device Security, GSM and UMTS Security, IEEE 802.11/802.11i Wireless LAN

Security, VPN Security

5 Legal and Ethical issues

7

L1, L2, L3,

L4, L5 Cybercrime and its types, Intellectual property, Privacy, Ethical issues

Protecting Programs and Data, Information and the Law, Rights of Employees and

Employers, Redress for Software Failures, Computer Crime, Ethical Issues in

Computer Security, case studies of ethics

6 Digital Forensics

12

L1, L2, L3,

L4

Introduction to Digital Forensics, Acquiring Volatile Data from Windows and Unix

systems, Forensic Duplication Techniques, Analysis of forensic images using open

source tools like Autopsy and SIFT, Investigating logs from Unix and windows

systems, Investigating Windows Registry

Total Hours 52

Online References:

Sr.

No.


Covered

1. https://www.owasp.org/in

dex.php/Main_Page

https://www.owasp.org/index.php/Category:OWASP_Top_

Ten_Project M1-M2

2. https://www.tutorialspoint

.com/index.htm

https://www.tutorialspoint.com/operating_system/os_securi

ty M2-M3

3. https://www.tutorialspoint

.com/index.htm

https://www.tutorialspoint.com/wireless_security/ M4

4. https://pressbooks.com/ https://bus206.pressbooks.com/chapter/chapter-12-the-

ethical-and-legal-implications-of-information-systems/ M5

5. https://www.open.edu/ope

nlearn/

https://www.open.edu/openlearn/science-maths-

technology/digital-forensics/content-section-4.3 M6


Practical

Number


levels as per

blooms

Taxonomy

1

Basic Experiments

Explain vulnerability scanning using Nessus,

Nikto (Kali Linux)

2

L1, L2

2 Illustrate web-application vulnerabilities using

open source tools like Wapiti, browser

exploitation framework (BeEf), etc.

2 L1, L2

3 Idebtify SQL injection vulnerabilities in a

website database using SQLMap

2 L1, L2, L3

4

Design Experiments

Apply Installation step and use a security app

on an Android mobile (e.g. Droidcrypt)

2

L1, L2, L3

5 Make use of forensics tools in Kali Linux for

acquiring, analyzing and duplicating data: dd,

dcfldd, foremost, scalpel, debugfs, wireshark,

tcptrace, tcpflow

2 L1, L2, L3

6

Analyze forensic images using open source

tools like Autopsy, SIFT, FKT Imager

2

L1, L2, L3, L4

7 Make use of steganographic tools like

OpenStego, to detect data hiding or

unauthorized file copying

2 L1, L2, L3

8 Make use Password cracking using tools like

John the Ripper/Cain and Abel/ Ophcrack to

detect weak passwords.

2 L1, L2, L3

9 Analyze static code using open source tools

like RATS, Flawfinder etc.

2 L1, L2, L3, L4

10 Apply a penetration testing using Metasploit

(Kali Linux)

2 L1, L2, L3

11

Case Studies

1. Exploring Authentication and access

control using RADIUS, TACACS and

TACACS+

2. Case Study on Stegonographic Tools

3. Case Study on latest Digital Forensic

Tools

4

L1, L2, L3, L4

https://www.owasp.org/index.php/Main_Page

https://www.owasp.org/index.php/Main_Page

https://www.owasp.org/index.php/Category:OWASP_Top_Ten_Project

https://www.owasp.org/index.php/Category:OWASP_Top_Ten_Project

https://www.tutorialspoint.com/index.htm


https://www.tutorialspoint.com/operating_system/os_security

https://www.tutorialspoint.com/operating_system/os_security



https://www.tutorialspoint.com/wireless_security/

https://pressbooks.com/

https://bus206.pressbooks.com/chapter/chapter-12-the-ethical-and-legal-implications-of-information-systems/

https://bus206.pressbooks.com/chapter/chapter-12-the-ethical-and-legal-implications-of-information-systems/

https://www.open.edu/openlearn/

https://www.open.edu/openlearn/

https://www.open.edu/openlearn/science-maths-technology/digital-forensics/content-section-4.3

https://www.open.edu/openlearn/science-maths-technology/digital-forensics/content-section-4.3

12 Mini/Minor

Projects/

1. Application Security

2. Stenography

3. Authentication Mechanisms

4. Android Security Application

5. Vulnerability Scanner

6 L1, L2, L3,

L4,L5, L6

Total Hours 30



Course Name :Department Level Optional Course -III (Big

Data Analytics)





(100)

Practical/Oral

(25)

Term

Work (25)

Total


Hours

Credits

IA ESE PR/OR TW

150 4 - 2 6 5 20 80 25 25





Prerequisite: Database Management System, Data Warehouse and Mining, Machine Learning

Course Objective:Thecourse intends to provide an overview of an exciting growing field of big data

analytics and equip the students with programming skills to solve complex real world problems using big

data technologies.


Sr.

No.


attainment as per

Bloom’s Taxonomy

1 Outline the key issues in big data management and its associated

applications for business decisions and strategy.

L1, L2

2 Develop problem solving and critical thinking skills in fundamental

enabling techniques like Hadoop, Map-reduce and NoSQL in big data

analytics.

L1, L2, L3

3 Collect, manage, store, query and analyze various forms of Big Data. L1, L2, L3, L4

4 Interpret business models and scientific computing paradigms, and apply

software tools for big data analytics.

L1, L2, L3, L4, L5

5 Appraise adequate perspectives of big data analytics in various

applications like recommender systems, social media applications etc...

L1, L2, L3, L4, L5

6 Solve Complex real world problems in various applications like

recommender systems, social media applications, health and medical

systems, etc.

L1, L2, L3

Detailed Syllabus:

Module

No.


attainment as per

Bloom’s Taxonomy

1 Introduction to Big Data and Hadoop 6 L1, L2

Introduction to Big Data, Big Data characteristics, types of Big Data,

Traditional vs. Big Data business approach, Case Study of Big Data

Solutions.

Concept of Hadoop, Core Hadoop Components; Hadoop Ecosystem

2 Hadoop HDFS and MapReduce 10

L1, L2, L3 Distributed File Systems: Physical Organization of Compute Nodes,

Large-Scale File-System Organization.

MapReduce: The Map Tasks, Grouping by Key, The Reduce Tasks,

Combiners, Details of MapReduce Execution, Coping With Node

Failures.

Algorithms Using MapReduce: Matrix-Vector Multiplication by

MapReduce, Relational-Algebra Operations, Computing Selections by

MapReduce, Computing Projections by MapReduce, Union,

Intersection, and Difference by MapReduce

Hadoop Limitations.

3 NoSQL 6 L1, L2, L3, L4

Introduction to NoSQL, NoSQL Business Drivers,

NoSQL Data Architecture Patterns: Key-value stores, Graph stores,

Column family (Bigtable) stores, Document stores, Variations of NoSQL

architectural patterns, NoSQL Case Study

NoSQL solution for big data, Understanding the types of big data

problems;Analyzing big data with ashared-nothingarchitecture; Choosing

distribution models: master-slave versus peer-to- to-peer; Four ways that

NoSQL systems handle big data problems

4 Mining Data Streams 12 L1, L2, L3, L4, L5

The Stream Data Model: A Data-Stream-Management System,

Examples of Stream Sources, Stream Queries, Issues in Stream

Processing, Sampling Data techniques in a Stream, Filtering Streams:

Bloom Filter with Analysis, Counting Distinct Elements in a Stream,

Count-Distinct Problem, Flajolet-Martin Algorithm, Combining

Estimates, Space Requirements,

Counting Frequent Items in a Stream, Sampling Methods for

Streams, frequent Itemsets in Decaying Windows, Counting Ones in a

Window: The Cost of Exact Counts, TheDatar-Gionis-Indyk-Motwani

Algorithm, Query Answering in the DGIM Algorithm, Decaying

Windows.

5 Finding Similar Items and Clustering 8 L1, L2, L3, L4, L5

Distance Measures: Definition of a Distance Measure, Euclidean

Distances, Jaccard Distance, Cosine Distance, Edit Distance, Hamming

Distance.CURE Algorithm, Stream-Computing , A Stream-Clustering

Algorithm,Initializing& Merging Buckets, Answering Queries

6 Real-Time Big Data Models 10 L1, L2, L3

PageRank Overview, Efficient computation of PageRank: PageRank

Iteration Using MapReduce, Use of Combiners to Consolidate the

Result Vector

A Model for Recommendation Systems, Content-Based

Recommendations, Collaborative Filtering


Sr.

No.


1 Mining of Massive Datasets AnandRajaraman

and Jeff Ullman

Cambridge

University Press

First

Edition

2012

2 Hadoop in Practice Alex Holmes

Manning Press,

Dreamtech Press Second

Edition

2015

3 Making Sense of NoSQL- A

guide for managers and the rest of

us

Dan Mcary and

Ann Kelly

Manning Press First

Edition

2010

4 Taming The Big Data Tidal

Wave: Finding Opportunities In

Huge Data Streams With

Advanced Analytics

Bill Franks

John Wiley &

Sons

First

Edition

2012

Online References:

Sr.

No.

Website Name URL Modules Covered

1 www.mmds.org http://www.mmds.org M1-M6

2 www.guru99.com https://www.guru99.com/bigdata-tutorials.html M1,M2

3 www.edureka.co https://www.edureka.co/blog/hadoop-tutorial/ M1, M2

4 www.tutorailride.com https://www.tutorialride.com/big-data-analytics M1-M6


Practical

Number

Type of

Experiment

Practical/ Experiment Topic Hrs. Cognitive

levels as per

blooms

Taxonomy

1

Basic Experiments

Explain Hadoop Ecosystem

2

L1, L2

2 Experiment with basic programs of

Hadoop

2 L1, L2, L3

3 Make use of Sqoop tool to transfer data

between Hadoop and relational database

servers.

2 L1, L2, L3

4 Design

Experiments

Apply Installation and configuration steps

ofMongoDB/Cassandra/HBase to execute

NoSQL commands

2 L1, L2, L3

5 Apply Map Reduce to Word count

problem

2

L1, L2, L3

6 Experiment withHadoop Map-

Reduce/PySpark

2 L1, L2, L3

Social Networks as Graphs, Clustering of Social-Network Graphs,

Direct Discovery of Communities in a social graph.

Total Hours 52

http://www.mmds.org/

https://www.guru99.com/bigdata-tutorials.html

https://www.edureka.co/blog/hadoop-tutorial/

https://www.tutorialride.com/big-data-analytics

7 Develop clustering algorithm K-

means/CURE using MapReduce

2 L1, L2, L3

8 ApplyMap- Reduce to implement Matrix

multiplication, Aggregates, joins, sorting,

searching

2

L1, L2, L3

9 Develop DGIM algorithm/ Bloom Filter

using any programming language

2

L1, L2, L3

10 DevelopPageRank algorithm 2 L1, L2, L3

11 Advanced

Experiments

DevelopHIVE Database and Descriptive

analytics-basic statistics, visualization

using HIVE/PIG/R

2 L1, L2, L3

12 Apply R/Scilab/rapid miner to implement

predictive analytics techniques

(regression/time series)

2 L1, L2, L3

13

Mini/Minor

Projects/ Seminar/

Case Studies

1. Twitter data analysis

2. fraud detection

3. Text Mining

4. Opinion mining

5. Fraud detection analysis

6. Similar topic detection analysis

4

L1, L2, L3,

L4,L5, L6

14 Paper writing on

Different Big data

analysis techniques

in real life

Identify research topics in Big data

analytics and write a research paper

2

L1, L2, L3, L4

Total Hours 30



Course Name :Department Level Optional Course -

III(Robotics)





(100)

Practical/Oral

(25)

Term

Work (25)

Total


Hours


150

4 - 2 6 5 20 80 25 25





Prerequisite: Engineering Mathematics

Course Objective:Thecourse intends to introduce the principles of robotics, and apply mathematical

Kinematic modeling for manipulation of Robot in 3-D Space, It will also use various actuator and sensor to

provide vision for proper task planning of the Robot.


Sr.

No.

Course Outcomes Cognitive levels

of attainment as

per Bloom’s

Taxonomy

1 Outline typical robot and its characteristics. L1, L2

2 Analyze kinematics parameters of robotic manipulator. L1, L2, L3, L4

3 Identify actuators, sensors and control of a robot for different applications. L1, L2, L3

4 Analyze motion of the robot for task planning L1, L2, L3, L4

5 Apply Robotics to solve day to day problems using vision algorithms. L1, L2, L3

6 Develop an Expert system of Robotics using Fuzzy logic controller L1, L2, L3

Detailed Syllabus:

Module

No.

Topics Hrs. Cognitive levels

of attainment as

per Bloom’s

Taxonomy

1 Introduction and Fundamentals of Robotics

6

L1, L2

Types of automation, Introduction, definition of a Robot, Classification

of Robots, Robotics, History of Robotics, Advantages and Disadvantages

of Robots, Robot Applications

Tasks involved in Robotics, Robot Components, Robot characteristics

and classification, Degrees of Freedom, Robot joints, Robot Coordinates,

Robot Reference frames, Programming Modes, Robot Workspace, Work

Envelop.

2 Direct and Inverse Kinematics

12

L1, L2, L3, L4

Direct (Forward) Kinematics: Homogeneous coordinates, Link

coordinates, Coordinate frame, coordinate transform, Arm equations, An

example – Four Axis SCARA.

Inverse Kinematics: Inverse kinematics problem, Tool Configuration,

An example – Four Axis SCARA.

3 Sensors, Actuators and Drive Systems

4

L1, L2, L3

Sensors: Characteristics, Utilization, Types - Position, Velocity,

Acceleration, Force and Pressure, Torque, Visible Light and Infrared,

Touch and Tactile, Proximity, Range Finders sensors.

Actuators and Drive System: Characteristics, Hydraulic Actuators,

Pneumatic Devices, Electric Motors

4 Robot Task and Motion Planning

11

L1, L2, L3, L4

Reactive Paradigms: Overview, Attributes of reactive paradigm

Task level programming, Uncertainty, Configuration Space, Gross

motion planning, Fine-motion planning, Simulation of Planner motion,

Source and goal scene, Task planner Simulation.

Robot Motion Planning: Concept of motion planning, BUG 1, BUG 2

and Tangent Bug Algorithms

5 Robot Vision

11

L1, L2, L3

Image Representation, Template Matching, Polyhedral Objects

Shape Analysis, Iterative Processing

Perspective Transformations, Structured Illumination , Camera

Calibration

6 Expert Systems, Robot Language and Fuzzy Logic

8

L1, L2, L3

Introduction to Expert Systems, Expert system Characteristics, Robot

as Expert System, Robot Languages: Classification of Robot

Languages, Computer Control and Robot Software, VAL System, and

Language

Introduction, Fuzzy set, Fuzzification, Fuzzy Inference Rule Base,

Defuzzification, Applications of Fuzzy Logic in Robotics.

Total Hours 52


Sr.

No.


1 Introduction Robotics - Analysis, Control,

Applications

Saeed B. Niku Wiley India Second

Edition

2010

2 Fundamentals of Robotics Robert J. Schilling Pearson First

Edition

2007

3 Introduction to AI robotics Robin Murphy PHI Second

Edition

2000

4 Robotics Technology and Flexible

Automation

S. R. Deb TMH Second

Edition

2002

Online References:

Sr.

No.


Covered

1 https://onlinelibrary.wil

ey.com

https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-

8659.1140189

M1-M2

2 https://link.springer.co

m

https://link.springer.com/chapter/10.1007/978-1-4615-

2353-6_6

M6

3 http://www.aishack.in http://www.aishack.in/tutorials/obstacle-avoidance-bug-

algorithm/

M4


Practical

Number


levels as per

blooms

Taxonomy

1

Basic Experiments

Illustrate Representation of Various Robots

and there all Specification (Study

Experiment)

2

L1, L2

2 Demonstrate 5 DOF Articulated Robot

through code

2 L1, L2

3 Make use of Y,P,R to develop basic

Composite Rotation matrix

2 L1, L2, L3

4

Design Experiments

Make use of Y,P,R to develop homogenous

Rotation Matrix on basis of CRM

2

L1, L2, L3

5 To identify position and orientation of Direct

Kinematics of 2/3/4 Axis Robot

2 L1, L2, L3

6

To identify configuration space of Inverse

kinematics of 2/3/4 Axis Robot

2

L1, L2, L3

7 Develop BUG 1 and BUG 2 Algorithm to

detect obstacles

2 L1, L2, L3

8 Develop Tangent BUG Algorithm to detect

obstacles

2 L1, L2, L3

9 Apply Run Length Encoding for image

compression

2 L1, L2, L3

https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-8659.1140189

https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-8659.1140189

https://link.springer.com/chapter/10.1007/978-1-4615-2353-6_6

https://link.springer.com/chapter/10.1007/978-1-4615-2353-6_6

http://www.aishack.in/tutorials/obstacle-avoidance-bug-algorithm/

http://www.aishack.in/tutorials/obstacle-avoidance-bug-algorithm/

10 Apply Edge Detection Algorithm on to an

image

2 L1, L2, L3

11 Apply Shrink and Swell operator on to an

image

2 L1, L2, L3

12 Apply Rule based Fuzzification Model for

Washing Machine Problem

2 L1, L2, L3

13

Mini/Minor

Projects/ Seminar/

Case Studies

1. Design Robot Arm of SCARA Robot

2. Surveillance Robot

3. Designing a Robot Manipulator for

Pre defined Task

4. Detect Edge and Obstacle for Robot

Motion

5. Design a Simulation from Source to

Destination using Bounded

Deviation Algorithm

6. Create a Project to Simulate Task

Planning

6

L1, L2, L3, L4,

L5, L6

Total Hours 30

B.E. Semester–VII


Course Name:Institute Level Optional Course-I(Product Life

Cycle Management) Course Code: ILO 7011




(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-

MSE: Mid Semester Examination - Paper Duration – 1.5 Hours

SEE : Semester End Examination - Paper Duration - 3 Hours

Prerequisite: Product Design and Development, Quality and Reliability Engineering

Course Objective:The Course should be able to provide an exposure to new product development

program and guidelines for designing and developing a product and apply the knowledge of Product Data

Management & PLM strategies.


SN Course Outcomes Cognitive levels

of attainment as

per Bloom’s

Taxonomy

1 Illustrate knowledge about phases of PLM, PLM strategies and

methodology for PLM feasibility study and PDM implementation

L1, L2

2 Illustrate various approaches and techniques for designing and developing

products.

L1,L2

3 Apply product engineering guidelines / thumb rules in designing products

for moulding, machining, sheet metal working etc

L1, L2, L3

4 Acquire knowledge in applying virtual product development tools for

components, machining and manufacturing plant

L1, L2, L3

5 Apply Integration of Environmental Aspects in Product Design L1, L2, L3

6. Illustrate knowledge aboutLife Cycle Assessment and Life Cycle Cost

Analysis

L1, L2

Detailed Syllabus:

Module

No.

Topics Hrs Cognitive levels of

attainment as per

Bloom’s Taxonomy

1 Introduction to Product Lifecycle Management (PLM) and PLM

Strategies

10

L1, L2

Product Lifecycle Management (PLM), Need for PLM, Product Lifecycle

Phases, Opportunities of Globalization, Pre-PLM Environment, PLM Paradigm,

Importance & Benefits of PLM, Widespread Impact of PLM, Focus and

Application, A PLM Project, Starting the PLM Initiative, PLM Applications

Industrial strategies, Strategy elements, its identification, selection and

implementation, Developing PLM Vision and PLM Strategy , Change

management for PLM

2 Product Design

9

L1, L2

Product Design: Product Design and Development Process, Engineering Design,

Organization and Decomposition in Product Design, Typologies of Design

Process Models, Reference Model, Product Design in the Context of the Product

Development Process, Relation with the Development Process Planning Phase,

Relation with the Post design Planning Phase, Methodological Evolution in

Product Design, Concurrent Engineering, Characteristic Features of Concurrent

Engineering, Concurrent Engineering and Life Cycle Approach, New Product

Development (NPD) and Strategies, Product Configuration and Variant

Management, The Design for X System, Objective Properties and Design for X

Tools, Choice of Design for X Tools and Their Use in the Design Process

3 Product Data Management (PDM)

7

L1, L2, L3 Product Data Management (PDM):Product and Product Data, PDM systems and

importance, Components of PDM, Reason for implementing a PDM system,

financial justification of PDM, barriers to PDM implementation

4 Virtual Product Development Tools

7

L1, L2, L3 Virtual Product Development Tools: For components, machines, and

manufacturing plants, 3D CAD systems and realistic rendering techniques,

Digital mock-up, Model building, Model analysis, Modeling and simulations in

Product Design, Examples/Case studies

5

Integration of Environmental Aspects in Product Design

6

L1, L2, L3

Integration of Environmental Aspects in Product Design: Sustainable

Development, Design for Environment, Need for Life Cycle Environmental

Strategies, Useful Life Extension Strategies, End-of-Life Strategies, Introduction

of Environmental Strategies into the Design Process, Life Cycle Environmental

Strategies and Considerations for Product Design

6 Life Cycle Assessment and Life Cycle Cost Analysis

8

L1, L2

Life Cycle Assessment and Life Cycle Cost Analysis: Properties, and

Framework of Life Cycle Assessment, Phases of LCA in ISO Standards, Fields

of Application and Limitations of Life Cycle Assessment, Cost Analysis and the

Life Cycle Approach, General Framework for LCCA, Evolution of Models for

Product Life Cycle Cost Analysis. Introduction to Industry 4.0, Design

principles and Challenges , Applications of Industry 4.0

Total Hours 39


SN Title Authors Publisher Edition Year

1 Product Lifecycle

Management: Paradigm

for 21st Century Product

Realisation

John Stark Springer-

Verlag - 2004

2 Product Design for the

environment-A life cycle

approach

Fabio Giudice, Guido

La Rosa,

AntoninoRisitano

Taylor &

Francis - 2006

3 Product Life Cycle

Management

SaaksvuoriAntti,

ImmonenAnselmie

Springer,

Dreamtech - -

4 Product Lifecycle

Management: Driving the

next generation of lean

thinking

Michael Grieve Tata

McGraw-

Hill, - 2006

Online References:

S. No. Website Name URL Modules

Covered

1 www.nptel.ac.in https://nptel.ac.in/courses/110104070/9 M1-M6

2 www.amieindia.in https://www.amieindia.in/study-

materials/product-life-cycle.pdf

M1, M5, M6

https://nptel.ac.in/courses/110104070/9

https://www.amieindia.in/study-materials/product-life-cycle.pdf

https://www.amieindia.in/study-materials/product-life-cycle.pdf

B.E. Semester–VII


Course Name:Institute Level Optional Course-I(Reliability

Engineering) Course Code: ILO 7012




(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-

MSE: Mid Semester Examination - Paper Duration – 1.5 Hours

SEE : Semester End Examination - Paper Duration - 3 Hours

Prerequisite: Product Design and Development, Quality and Reliability Engineering

Course Objective: To impart various aspects of probability theory, system reliability, maintainability,

availability and FMEA procedure.


SN Course Outcomes Cognitive Levels as per

Bloom’s Taxonomy

1 Understand and apply the concept of Probability to engineering problems L1,L2,L3

2 Apply various reliability concepts to calculate different reliability parameters L1,L2,L3,L4

3 3Estimate the system reliability of simple and complex systems L1,L2,L3

4 Carry out a Failure Mode Effect and Criticality Analysis L1,L2,L3,L4

Detailed Syllabus:

Module

No.

Topics Hrs Cognitive Levels as

per Bloom’s

Taxonomy

1

Probability theory

8

L1,L2,L3

Probability: Standard definitions and concepts; ConditionalProbability,

Baye’s Theorem. Probability Distributions: Central tendency and

Dispersion; Binomial, Normal, Poisson, Weibull, Exponential, relations

between them and their significance. Measures of Dispersion: Mean,

Median, Mode, Range, Mean Deviation, Standard Deviation, Variance,

Skewness and Kurtosis.

2 Reliability Concepts 08 L1,L2,L3


S.

No


1 Reliability Engineering”, L.S. Srinath, “Affiliated East-Wast

Press (P) Ltd

3rdEdition 1985

2 “Reliability and

Maintainability Engineering

Charles E. Ebeling Tata McGraw Hill. 4th Edition 2015

3 Engineering Reliability B. S. Dhillion C. Singh, John Wiley & Sons 5th edition 1980

4 Practical Reliability Engg.”, P.D.T. Conor John Wiley & Sons 3rd Edition

1985.

5. Reliability in Engineering

Design

K.C. Kapur, L.R.

Lamberson

John Wiley & Sons. 3rdEdition 1989

6. Probability and Statistics Murray R. Spiegel Tata McGraw-Hill

Publishing Co. Ltd.

5th edition 1980

Reliability Concepts: Reliability definitions, Importance of Reliability,

Quality Assurance and Reliability, Bath Tub Curve.

Failure Data Analysis: Hazard rate, failure density, Failure Rate, Mean Time

ToFailure (MTTF), MTBF, Reliability Functions.

Reliability Hazard Models: Constant Failure Rate, Linearly increasing,

TimeDependent Failure Rate, Weibull Model. Distribution functions and

reliability analysis.

3

System Reliability:

06 L1,L2,L3,L4 System Reliability: System Configurations: Series, parallel, mixed

configuration, k out

of n structure, Complex systems

4

Reliability Improvement:

L1,L2 Reliability Improvement: Redundancy Techniques: Element redundancy,

Unit redundancy, Standby redundancies. Markov analysis.

System Reliability Analysis – Enumeration method, Cut-set method,

Success, Path method, Decomposition method.

5

Maintainability and Availability

5

L1,L2,L3

Maintainability and Availability: System downtime, Design for

Maintainability:

Maintenance requirements, Design methods: Fault Isolation and self-

diagnostics, Partsstandardization and Interchangeability, Modularization and

Accessibility, Repair VsReplacement.

Availability – qualitative aspects.

6

Failure Mode, Effects and Criticality Analysis:

5 L1,L2

Failure mode effects analysis:severity/criticality analysis, FMECA

examples. Fault tree construction, basic symbols,development of functional

reliability block diagram, Fau1t tree analysis and Event tree Analysis

Total Hours 39

B.E. Semester–VII


Course Name :Institute Level Optional Course-I(Management

Information System)

Course Code :ILO 7013




(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-



Prerequisite: Database Design and Management

Course Objective:Thecourse intends to deliver the role of Management in Information Systems & to

understand the impact of these systems within an Organization to improve business performance and decision

making. It analyzes typical functional information systems, principal tools and technologies for accessing

information from databases & interpreting Ethical issues & Privacy for the same.


Sr.

No.


of attainment

as per Bloom’s

Taxonomy

1 Explain how information systems Transform Business L1, L2

2 Understand about Data and Knowledge Management L1, L2, L3

3 Analyze the Ethical issues and Privacy in Information Systems L1, L2, L3, L4

4 Understand the principal tools and technologies for accessing information from

databases to improve business performance and decision making

L1, L2, L3

5 Analyze the types of systems used for enterprise-wide knowledge management and

how they provide value for businesses

L1, L2, L3, L4

6 Analyze the impact of information systems have on an organization L1, L2, L3, L4

Detailed Syllabus:


Sr.

No.


1. Management Information Systems Kelly Rainer, Brad Prince Wiley Sixth Edition 2011

2. Management Information Systems K.C. Laudon and J.P. Laudon Prentice Hall Tenth Edition 2007

3. Managing Information Systems:

Strategy and Organization

D. Boddy, A. Boonstra Prentice Hall Tenth Edition 2008

Online References:

Sr.

No.


Covered 1. https://www.tutorialspoint.co

m/index.htm

https://www.tutorialspoint.com/management_information_system/ M1

2. https://www.tutorialspoint.co

m/index.htm

https://www.tutorialspoint.com/management_information_system/informati

on_need_objective.htm

M2


m/index.htm

https://www.tutorialspoint.com/management_information_system/mis_secu

rity_and_ethical_issues.htm

M3


m/index.htm

https://www.tutorialspoint.com/management_information_system/system_d

evelopment_life_cycle.htm

M4

5. https://pressbooks.com/ https://bus206.pressbooks.com/chapter/chapter-13-future-trends-in-

information-systems/

M5


m/index.htm

https://www.tutorialspoint.com/management_information_system/business

_continuity_planning.htm

M6

List of Practical/ Experiments:NA

Module

No.


attainment as per

Bloom’s Taxonomy

1 Introduction To Information Systems (IS)

4

L1, L2

Computer Based Information Systems, Impact of IT on organizations,

Importance of IS to Society. Organizational Strategy, Competitive Advantages

and IS

2 Data and Knowledge Management

7

L1, L2, L3

Database Approach, Big Data, Data warehouse and Data Marts, Knowledge

Management Business intelligence (BI): Managers and Decision Making, BI for

Data analysis and Presenting Results

3 Ethical issues and Privacy

7

L1, L2, L3, L4 Information Security. Threat to IS, and Security Controls

4 Social Computing (SC)

7

L1, L2, L3 Web 2.0 and 3.0, SC in business-shopping, Marketing, Operational and Analytic

CRM, E-business and E-commerce – B2B B2C. Mobile commerce.

5

Wired and Wireless Technology

6

L1, L2, L3, L4 Computer Networks Wired and Wireless Technology,Pervasive computing,

Cloud computing model.

6 Information System within Organization

8

L1, L2, L3, L4

Transaction Processing Systems, Functional Area Information System, ERP and

ERP support of Business Process. Acquiring Information Systems and

Applications: Various System development life cycle models

Total Hours 39



https://www.tutorialspoint.com/management_information_system/



https://www.tutorialspoint.com/management_information_system/information_need_objective.htm

https://www.tutorialspoint.com/management_information_system/information_need_objective.htm



https://www.tutorialspoint.com/management_information_system/mis_security_and_ethical_issues.htm

https://www.tutorialspoint.com/management_information_system/mis_security_and_ethical_issues.htm



https://www.tutorialspoint.com/management_information_system/system_development_life_cycle.htm

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B.E. Semester–VII


Course Name :Institute Level Optional Course-I(Design of

Experiments)





(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-



Prerequisite:

Course Objective:The course intends to study issues and principles of Design of Experiments (DOE)

and list the guidelines for designing experiments to become familiar with methodologies that can be used in

conjunction with experimental designs for robustness and optimization


SN Course Outcomes Cognitive levels of

attainment as per Bloom’s

Taxonomy

1 Plan data collection, to turn data into information and to make

decisions that lead to appropriate action

L1, L2, L3, L4

2 Apply the methods taught to real life situations L1, L2, L3

3 Plan, analyze, and interpret the results of experiments L1, L2, L3, L4

Detailed Syllabus:

Modul

e No.


levels of

attainment

as per

Bloom’s

Taxonomy

1 Introduction

6

L1, L2

Strategy of Experimentation, Typical Applications of Experimental Design,

Guidelines for Designing Experiments, Response Surface Methodology

2 Fitting Regression Models



1 Response Surface Methodology:

Process and Product

Optimization using Designed

Experiment

Raymond H.

Mayers, Douglas

C. Montgomery,

Christine M.

Anderson-Cook

Wiley & Sons 3rd

Edition

2001

2 Design and Analysis of

Experiment

D.C. Montgomery John Wiley &

Sons

5th

edition

2001

3 Statics for Experimenters:

Design, Innovation and

Discovery,.

George E P Box, J

Stuart Hunter,

William G Hunter

Wiley 2nd Ed 2005

Online Resources:

S.

No.


Covered

1 https://www2.isye.gate

ch.edu https://www2.isye.gatech.edu/~yxie77/isye2028/lecture12.pdf

M1, M2

2 http://reliawiki.org http://reliawiki.org/index.php/Multiple_Linear_Regression_An

alysis

M2

3 https://www.stat.washi

ngton.edu

https://www.stat.washington.edu/pds/stat502/LectureNotes/2k.

factorial.intro.pdf

www.math.montana.edu/jobo/st578/sec6.pdf

M3,M5

4 https://www2.isye.gate

ch.edu

https://www2.isye.gatech.edu/~jeffwu/isye6413/unit_08_12spr

ing.pdf

M6

Linear Regression Models, Estimation of the Parameters in Linear Regression

Models, Hypothesis Testing in Multiple Regression, Confidence Intervals in

Multiple Regression, Prediction of new response observation, Regression

model diagnostics, Testing for lack of fit.

8

L1, L2, L3,

L4

3 Two-Level Factorial Designs

7

L1, L2, L3,

L4 The 22 Design, The 23 Design , The General 2k Design, A Single Replicate of

the 2k Design, The Addition of Center Points to the 2k Design, Blocking in

the 2k Factorial Design Split-Plot Designs

4 Two-Level Fractional Factorial Designs 7 L1, L2, L3,

L4 The One-Half Fraction of the 2k Design, The One-Quarter Fraction of the 2k

Design, The General 2k-p Fractional Factorial Design, Resolution III Designs,

Resolution IV and V Designs, Fractional Factorial Split-Plot Designs

5 Response Surface Methods and Designs 7 L1, L2, L3,

L4 Introduction to Response Surface Methodology, The Method of Steepest

Ascent, Analysis of a Second-Order Response Surface, Experimental Designs

for Fitting Response Surfaces

6 Taguchi Approach 4 L1, L2, L3

Crossed Array Designs and Signal-to-Noise Ratios, Analysis Methods, Robust

design examples

Total Hours 39

http://mathworld.wolfram.com/MethodofSteepestDescent.html

http://mathworld.wolfram.com/MethodofSteepestDescent.html

http://www.math.montana.edu/jobo/st578/sec6.pdf

https://www2.isye.gatech.edu/~jeffwu/isye6413/unit_08_12spring.pdf

https://www2.isye.gatech.edu/~jeffwu/isye6413/unit_08_12spring.pdf

List of Practical/ Experiments: NA

B.E. Semester–VII

Approved by Ad-Hoc Board of Studies and Academic Council under TCET Autonomy


Course Name :Institute Level Optional Course-I(Operation

Research)





(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-



Prerequisite: Engineering Mathematics

Course Objective: Course should deliver the optimization techniques so that student should be able to

optimize any engineering product or process.

Course Outcomes: Upon completion of the course students will be able to:

SN Course Outcomes Cognitive levels of

attainment as per

Bloom’s Taxonomy

1 Understand the theoretical workings of the simplex method, the relationship

between a linear program and its dual, including strong duality and

complementary slackness.

L1, L2, L3

2 Perform sensitivity analysis to determine the direction and magnitude of

change of a model’s optimal solution as the data change

L1, L2, L3

3 Solve specialized linear programming problems like the transportation and

assignment problems, solve network models like the shortest path, minimum

spanning tree, and maximum flow problems

L1, L2, L3, L4

4 Understand the applications of integer programming and a queuing model

and compute important performance measures

L1, L2, L3

5 Apply conflict between two players L1, L2, L3, L4

6 Apply EOQ model in inventory L1, L2, L3, L4, L5

Detailed Syllabus:

Module

No.


attainment as per

Bloom’s Taxonomy

1

Introduction to Operations Research

14

L1, L2, L3

Introduction, , Structure of the Mathematical Model, Limitations of

Operations Research

Linear Programming:

Introduction, Linear Programming Problem, Requirements of LPP,

Mathematical Formulation of LPP, Graphical method, Simplex Method

Penalty Cost Method or Big M-method, Two Phase Method, Revised

simplex method, Duality, Primal – Dual construction, Symmetric and

Asymmetric Dual, Weak Duality Theorem, Complimentary Slackness

Theorem, Main Duality Theorem, Dual Simplex Method, Sensitivity

Analysis

1.1

Transportation Problem:

Formulation, solution, unbalanced Transportation problem. Finding

basic feasible solutions – Northwest corner rule, least cost method and

Vogel’s approximation method. Optimality test: the stepping stone

method and MODI method

1.2

Assignment Problem Introduction, Mathematical Formulation of the Problem, Hungarian

Method Algorithm, Processing of n Jobs Through Two Machines and m

Machines, Graphical Method of Two Jobs m Machines Problem Routing

Problem, Travelling Salesman Problem

Integer Programming Problem Introduction, Types of Integer Programming Problems, Gomory’s

cutting plane Algorithm, Branch and Bound Technique. Introduction to

Decomposition algorithms.

2

Queuing models:

05

L1, L2, L3 queuing systems and structures, single server and multi-server models,

Poisson input, exponential service, constant rate service, finite and

infinite population

3 Simulation:

05

L1, L2, L3, L4 Introduction, Methodology of Simulation, Basic Concepts, Simulation

Procedure, Application of Simulation Monte-Carlo Method: Introduction,

Monte-Carlo Simulation, Applications of Simulation, Advantages of

Simulation, Limitations of Simulation

4

Dynamic programming.

6

L1, L2, L3, L4 Characteristics of dynamic programming. Dynamic programming

approach for Priority Management employment smoothening, capital

budgeting, Stage Coach/Shortest Path, cargo loading and Reliability

problems.

Game Theory.


SN Title Authors Publisher Edition Year

1

Operations Research - An

Introduction

Taha, H.A.

Prentice Hall,

7th Edition,

2002-

2

Operations Research:

Principles and Practice",

Ravindran, A, Phillips

John Willey

and Sons

2nd Edition

-

2009

3

Introduction to

Operations Research

Hiller, F. S. and

Liebermann

McGraw Hill

- -

4

Operations Research

S. D. Sharma

KedarNath

Ram Nath-

Meerut

- -

B.E. Semester–VII

5 Competitive games, rectangular game, saddle point, minimax (maximin)

method of optimal strategies, value of the game. Solution of games with

saddle points, dominance principle. Rectangular games without saddle

point – mixed strategy for 2 X 2 games.

10

L1, L2, L3

6

Inventory Models

08

L1, L2, L3, L4, L5

Classical EOQ Models, EOQ Model with Price Breaks, EOQ with

Shortage, Probabilistic EOQ Model,


Course Name :Institute Level Optional Course-I(Cyber Security

and Laws)





(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-



Prerequisite: Cryptography and network security

Course Objective: The Course intends to deliver the fundamentals of cyber law, intellectual property,

cybercrimes, trademarks, domain theft, tools used in cyber security and analyze security policies, protocols

applied in Indian IT Act 2008, security standards compliances.


SN Course Objectives Cognitive levels

of attainment as

per Bloom’s

Taxonomy

1 Understand the concept of cybercrime and its effect on outside world

L1,L2

2 Interpret and apply IT law in various legal issues , Analyze security

challenges and issues

L1,L2,L3

3 Understand and analyze various attack using tools like wire shark , key

logger etc

L1,L2

4 Distinguish different aspects of cyber law L1,L2,L3,L4

5 Study India IT Act and analyze different case studies L1,L2,L3,L4

6 Apply Information Security Standards compliance during software

design and development

L1,L2,L3,L4

Detailed Syllabus:

Books and References

Sr.

No


1 Cyber Security Nina Godbole,

SunitBelapure Wiley India ,New Delhi 2nd 2011

Modul

e No.

Topics Hrs Cognitive

levels of

attainment as

per Bloom’s

Taxonomy

1 Introduction to Cybercrime: 4

L1,L2 Introduction to Cybercrime: Cybercrime definition and origins of the world,

Cybercrime and information security, Classifications of cybercrime, Cybercrime

and the Indian ITA 2000, A global Perspective on cybercrimes.

2

Cyber offenses & Cybercrime:

9 L1,L2

Cyber offenses & Cybercrime: How criminal plan the attacks, Social Engg, Cyber

stalking, Cyber café and Cybercrimes, Bot nets, Attack vector, Cloud computing,

Proliferation of Mobile and Wireless Devices, Trends in Mobility, Credit Card

Frauds in Mobile and Wireless Computing Era, Security Challenges Posed by

Mobile Devices, Registry Settings for Mobile Devices, Authentication Service

Security, Attacks on Mobile/Cell Phones, Mobile Devices: Security Implications for

Organizations, Organizational Measures for Handling Mobile, Devices-Related

Security Issues, Organizational Security Policies and Measures in Mobile

Computing Era, Laptops

3

Tools and Methods Used in Cyber line

6 L1,L2 Phishing, Password Cracking, Key loggers and Spywares, Virus and Worms,

Steganography, DoS and DDoS Attacks, SQL Injection, Buffer Over Flow, Attacks

on Wireless Networks, Phishing, Identity Theft (ID Theft)

4 The Concept of Cyberspace

8 L1,L2,L3,L4

E-Commerce , The Contract Aspects in Cyber Law ,The Security Aspect of Cyber

Law ,The Intellectual Property Aspect in Cyber Law , The Evidence Aspect in Cyber

Law , The Criminal Aspect in Cyber Law,Global Trends in Cyber Law , Legal

Framework for Electronic Data Interchange Law Relating to Electronic Banking ,

The Need for an Indian Cyber Law

5 Indian IT Act.

6 L1,L2,L3,L4 Cyber Crime and Criminal Justice: Penalties, Adjudication and Appeals Under

the IT Act, 2000, IT Act. 2008 and its Amendments

6 Information Security Standard compliances

6 L1,L2,L3,L4 SOX, GLBA, HIPAA, ISO, FISMA, NERC, PCI.

Total Hours 39

2

The Indian Cyber Law Suresh T.

Vishwanathan Bharat Law House,New

Delhi

2nd 2015

3 Cyber Law & Cyber

Crimes

Advocate Prashant

Mali

Snow White Publications,

Mumbai 2nd 2015

4 Information Systems

Security

Nina Godbole Wiley India, New Delhi 2nd 2014

5 Cyber Security &Global

Information Assurance

Kennetch J. Knapp Information Science

Publishing. 1st 2009

B.E. Semester–VII


Course Name :Institute Level Optional Course-I(Disaster

Management and Mitigation Measures)





(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-



Prerequisite: Analog Communication, Digital Communication, Computer Communication and Networks

Course Objective: Main objective of the subject is to understand causes of different types of disasters,

mitigation /rehabilitation measures and existing government policies and agencies.


SN Course Outcomes Cognitive levels of attainment

as per Bloom’s Taxonomy

1 Get to know natural as well as manmade disaster and their extent and

possible effects on the economy. L1, L2

2 Plan of national importance structures based upon the previous history. L1, L2

3 Get acquainted with government policies, acts and various organizational

structure associated L1, L2, L3

4 Get to know the simple do‘s and don‘ts in such extreme events and act

accordingly. L1, L2

Detailed Syllabus:

Module

No.


levels of

attainment

as per

Bloom’s

Taxonomy

1 Introduction 03

Definition of Disaster, hazard, global and Indian scenario, generalperspective,

importance of study in human life, Direct and indirecteffects of disasters, long term

effects of disasters. Introduction to global warming and climate change

L1, L2

2 Natural Disaster and Manmade disasters 09

Natural Disaster: Meaning and nature of natural disaster, Flood,Flash flood, drought,

cloud burst, Earthquake, Landslides,Avalanches, Volcanic eruptions,

Mudflow, Cyclone, Storm, StormSurge, climate change, global warming, sea level

rise, ozonedepletion, Manmade Disasters: Chemical, Industrial, Nuclear and Fire

Hazards.Role of growing population and subsequent industrialization,urbanization

and changing lifestyle of human beings in frequentoccurrences of manmade disasters

L1, L2

3 Disaster Management, Policy and Administration 06

Disaster management: meaning, concept, importance, objective ofdisaster

management policy, disaster risks in India, Paradigm shift indisaster management

Policy and administration:

Importance and principles of disaster management policies, commandand co-

ordination of in disaster management, rescue operations-howto start with and how to

proceed in due course of time, study offlowchart showing the entire process.

L1, L2

4 Institutional Framework for Disaster Management in India 06

Importance of public awareness, Preparation and execution ofemergency

management program. Scope and responsibilities ofNational Institute of Disaster

Management (NIDM) and Nationaldisaster management authority (NDMA) in India.

Methods andmeasures to avoid disasters, Management of casualties, set up of

emergency facilities, importance of effective communicationamongst different

agencies in such situations.Use of Internet and softwares for effective disaster

management. Applications of GIS, Remote sensing and GPS in this regard.

L1, L2

5 Financing Relief Measures 09

Ways to raise finance for relief expenditure, role of governmentagencies and NGO‘s

in this process, Legal aspects related to financeraising as well as overall management

of disasters. Various NGO‘sand the works they have carried out in the past on the

occurrence ofvarious disasters, Ways to approach these teams.International relief aid

agencies and their role in extreme events

L1, L2

6 Preventive and Mitigation Measures 06

Pre-disaster, during disaster and post-disaster measures in someevents in

general.Structural mapping: Risk mapping, assessment and analysis, sea walls and

embankments, Bio shield, shelters, early warning and communication.Non Structural

Mitigation: Community based disaster preparedness, risk transfer and risk financing,

capacity development and training, awareness and education, contingencyplans.Do‘s

and don‘ts in case of disasters and effective implementation of relief aids.

L1, L2

Total 39

Books & References:

SN Title Authors Publisher Year

1 Disaster Management

Harsh K.Gupta Universities Press

Publications 2003

2 Disaster Management: An Appraisal

of Institutional Mechanisms in India O.S.Dagur

Centre for land warfare

studies 2011

3 Introduction to International Disaster

Management

Damon Copolla

Butterworth

Heinemann Elsevier

Publications

2006

4 Disaster Management Handbook Jack Pinkowski

CRC Press Taylor and

Francis group 2008

5 Disaster management &

rehabilitation RajdeepDasgupta Mittal Publications 2007

6 Natural Hazards and Disaster

Management, Vulnerability and

Mitigation R B Singh

Rawat Publications

2006

7 Concepts and Techniques of GIS C.P.Lo Albert,

K.W. Yonng

Prentice Hall (India)

Publications.

2006

B.E. Semester–VII


Course Name :Institute Level Optional Course-I(Energy Audit

and Management)





(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-



Prerequisite:

Course Objective:The course intends to provide understanding of unwanted source of energy and

remedial measures for Energy Conservation through Energy Audit. In addition, subject analyses and

highlights the detailed audit procedures of various energy generation plants & establishments, Govt

initiatives and bodies associated with Electrical Energy Management.


SN Course Outcomes

Cognitive levels

of attainment as

per Bloom’s

Taxonomy

1 To identify and describe present state of energy conservation, security and

its importance.

L1, L2

2 To identify and describe the basic principles and methodologies adopted in

energy audit of energy generation establishment/plants.

L1, L2, L3, L4

3 To describe the energy performance evaluation of some common electrical

installations and identify the energy saving opportunities

L1, L2, L3, L4, L5

4 To describe the energy performance evaluation of some common thermal

installations and identify the energy saving opportunities

L1, L2, L3, L4, L5

5 To analyze the data collected during performance evaluation and

recommend energy saving measures

L1, L2, L3, L4,

L5, L6

Detailed Syllabus:

Module

No.

Topics Hrs.

Cognitive

levels of

attainment as

per Bloom’s

Taxonomy

1 Energy Scenario 05

L1 Present Energy Scenario, Energy Pricing, Energy Sector Reforms, Energy

Security, Energy Conservation and its Importance, EnergyConservationAct-2001

and its Features. Basics of Energy and itsvarious forms, Material and Energy

balance

2 Energy Audit Principles 08

L1, L2, L3

Definition, Energy audit- need, Types of energy audit, Energymanagement (audit)

approach-understanding energy costs, Benchmarking, Energy performance,

Matching energy use to requirement,Maximizing system efficiencies, Optimizing

the input energyrequirements, Fuel and energy substitution. Elements of

monitoring&targeting; Energy audit Instruments; Data and information-analysis.

Financial analysis techniques: Simple payback period, NPV, Returnon investment

(ROI), Internal rate of return (IRR)

3 Energy Management and Energy Conservation in ElectricalSystem 05

L1, L2, L3, L4

Electricity billing, Electrical load management and maximumdemand Control;

Power factor improvement, Energy efficientequipments and appliances, star

ratings.

Energy efficiency measures in lighting system, Lighting control:

Occupancy sensors, daylight integration, and use of intelligentcontrollers.

Energy conservation opportunities in: water pumps, industrialdrives,

induction motors, motor retrofitting, soft starters, variablespeed drives.

4 Energy Management and Energy Conservation in ThermalSystems 08

L1, L2, L3, L4

Review of different thermal loads; Energy conservation opportunitiesin: Steam

distribution system, Assessment of steam distributionlosses, Steam leakages,

Steam trapping, Condensate and flash steamrecoverysystem.General fuel

economy measures in Boilers and furnaces, Waste heatrecovery, use of

insulation- types and application. HVAC system: Coefficient of performance,

Capacity, factors affecting Refrigerationand Air Conditioning system

performance and savings opportunities.

5 Energy Performance Assessment 07

L1, L2, L3,

L4, L5 On site Performance evaluation techniques, Case studies based on: Motors and

variable speed drive, pumps, HVAC system calculations; Lighting System:

Installed Load Efficacy Ratio (ILER) method, Financial Analysis.

6 Energy conservation in Buildings 06

L1, L2, L3,

L4, L5 Energy Conservation Building Codes (ECBC): Green Building,LEED rating,

Application of Non-Conventional and RenewableEnergy Sources

Total 39

Books & References:

SNo. Title Authors Publisher Edition

1 Handbook of Electrical

Installation Practice

Geofry Stokes, Blackwell Science 2003

2 Designing with light: Lighting

Handbook

Anil Valia Lighting System 2010

3 Energy Management Handbook W.C. Turner John Wiley and

Sons

2007

4 Handbook on Energy Audits and

Management

Edited by A. K. Tyagi Tata Energy

Research Institute

(TERI).

2017

5 Energy Management Principles C.B.Smith Pergamon Press 2015

6 Energy Conservation Guidebook Dale R. Patrick, S. Fardo,

Ray E. Richardson

Fairmont Press

2015

7 Handbook of Energy Audits Albert Thumann, W. J.

Younger, T. Niehus,

CRC Press 2017

Online References:

S.

No. Website Name URL

Modules

Covered

1 energymanagertraining www.energymanagertraining.com M3

2 bee-india.nic www.bee-india.nic.in M2

B.E. Semester–VII


Course Name :Institute Level Optional Course-I(Development

Engineering)





(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


100

3 - - 3 3 20 80 -

-



Prerequisite: Civics, Ethics

Course Objectives:Course intend deliver introduction to characteristics of rural Society and the Scope, Nature

and Constraints of rural Development&exploration of human values ‘good’ professional, a ‘good’ society and a ‘good

life’ in the context of work life and the personal life of modern Indian professionals.


Sr.

No.


of attainment

as per Bloom’s

Taxonomy

1 Apply knowledge for Rural Development. L1, L2

2 Apply knowledge for Management Issues.. L1,L2

3 Apply knowledge for Initiatives and Strategies L1, L2, L3

4 Develop acumen for higher education and research. L1, L2, L3

5 Master the art of working in group of different nature. L1, L2, L3

6 Develop confidence to take up rural project activities independently L1, L2

Detailed Syllabus:

Module

No.


attainment as per

Bloom’s Taxonomy

1 Introduction to Rural Development

10

L1, L2

Introduction to Rural Development Meaning, nature and scope of

development; Nature of rural society in India; Hierarchy of settlements;

Social, economic and ecological constraints for rural development

Roots of Rural Development in India Rural reconstruction and

Sarvodayaprogramme before independence; Impact of voluntary effort

and Sarvodaya Movement on rural development; Constitutional

direction, directive principles; Panchayati Raj - beginning of planning

and community development; National extension services.

2 Rural Development Initiatives

9

L1, L2

Post-Independence rural Development BalwantRai Mehta Committee -

three tier system of rural local Government; Need and scope for

people’s participation and Panchayati Raj; Ashok Mehta Committee -

linkage between Panchayati Raj, participation and rural development

3 Rural Development Initiatives

7

L1, L2, L3 . Rural Development Initiatives in Five Year Plans Five Year Plans and

Rural Development; Planning process at National, State, Regional and

District levels; Planning, development, implementing and monitoring

organizations and agencies; Urban and rural interface - integrated

approach and local plans; Development initiatives and their

convergence; Special component plan and sub-plan for the weaker

section; Micro-eco zones; Data base for local planning; Need for

decentralized planning; Sustainable rural development.

4 Amendments

7

L1, L2, L3 Post 73rd Amendment Scenario 73rd Constitution Amendment Act,

including - XI schedule, devolution of powers, functions and finance;

Panchayati Raj institutions - organizational linkages; Recent changes in

rural local planning; Gram Sabha - revitalized Panchayati Raj;

Institutionalization; resource mapping, resource mobilization including

social mobilization; Information Technology and rural planning; Need

for further amendments.

5

Values and Science and Technology

6

L1, L2, L3

Values and Science and Technology Material development and its

values; the challenge of science and technology; Values in planning

profession, research and education.

Types of Values Psychological values — integrated personality; mental

health; Societal values — the modern search for a good society; justice,

democracy, rule of law, values in the Indian constitution; Aesthetic

values — perception and enjoyment of beauty; Moral and ethical

values; nature of moral judgment; Spiritual values; different concepts;

secular spirituality; Relative and absolute values; Human values—

humanism and human values; human rights; human values as freedom,

creativity, love and wisdom. Ethics


Sr.No. Title Authors Publisher Edition Year

1 Village Planning and

Rural Development

ITPI ITPI - -

2 Human Settlements Thooyavan, K.R. MA

Publication,

Chennai

-- 2005

3 Manual of Integrated

District Planning

Planning Commission Planning

Commission

--

2006

4 Normative Ethics in

Planning

How, E.

Journal of

Planning

Literature

Vol.5, No.2,

pp. 123-150

2017

Online References:

Sr.

No.


Covered

1 www.india.gov.in https://www.india.gov.in/my-government/constitution-

india/amendments/constitution-india-seventy-third-

amendment-act-1992

M1-M4

B.E. Semester–VII

6 Ethics Canons of ethics; ethics of virtue; ethics of duty; ethics of

responsibility; Work ethics; Professional ethics; Ethics in planning

profession, research and education

8 L1, L2

Total Hours 39


Course Name :Major Project-I Course Code : CSP701




(100)

Practical/Oral

(25)

Term Work

(25)

Total


Hours


75 - - 6 6 3 - - 25 50




completion of project (40%) and Attendance/Learning Attitude (20%)

Prerequisite: -

Course Objective:The Project work enables students to develop further skills and knowledge gained

during the programme by applying them to the analysis of a specific problem or issue, via a substantial piece

of work carried out over an extended period. For students to demonstrate proficiency in the design of a

research project, application of appropriate research methods, collection and analysis of data and presentation

of results.

Guidelines:

1. Project Topic:

To proceed with the project work it is very important to select a right topic. Project can be undertaken

on any subject addressing IT programme. Research and development projects on problems of practical

and theoretical interest should be encouraged.

Project work must be carried out by the group of at least two students and maximum three and must be

original.

Students can certainly take ideas from anywhere, but be sure that they should evolve them in the unique

way to suit their project requirements.

The project work can be undertaken in a research institute or organization/company/any business

establishment.

Student must consult internal guide along with external guide (if any) in selection of topic.

Head of department and senior staff in the department will take decision regarding selection of projects.

Student has to submit weekly progress report to the internal guide and whereas internal guide has to keep

track on the progress of the project and also has to maintain attendance report. This progress report can

be used for awarding term work marks.

In case of industry projects, visit by internal guide will be preferred.

2. Project Report Format:

At the end of semester a project report should preferably contain at least following details:-

Abstract

Introduction

Literature Survey

Survey Existing system

Limitation Existing system or research gap

Problem Statement and Objective

Scope

Proposed System

Analysis/Framework/ Algorithm

Details of Hardware & Software

Design details

Methodology (your approach to solve the problem)

Implementation Plan for next semester

Conclusion

References

3. Term Work:

Distribution of marks for term work shall be as follows:

a. Weekly Attendance on Project Day

b. Project work contribute

c. Project Report (Spiral Bound)

d. Term End Presentation (Internal)

The final certification and acceptance of TW ensures the satisfactory performance on the above aspects.

4. Oral & Practical :

Oral &Practical examination of Project-I should be conducted by Internal and External examiners

approved by University of Mumbai. Students have to give presentation and demonstration on the

Project I.


BE (ALL BRANCHES) SEM: VII

Course Name: Research Based Learning 3 Course Code:HSD-CSRBL701


Modes of Teaching / Learning / Weightage Assessment/Evaluation Scheme

Hours Per Week Presentation Report Term

Work


Hours

Credits IA ESE

IA ESE TW

Audit course evaluated by Teacher Guardian

Mid Semester Assessment for Term work will be on continuous basis

Prerequisite:Subject knowledge, Domain knowledge

Course Objectives: This course is focused to give basic aspects of Research and development, including research methodologies,

innovation, IPR, and entrepreneurship.


S.N. Course Outcome Cognitive level attainment as per

revised Bloom Taxonomy

1 Students will be to publish research paper. L1, L2, L3,L4

2 Student will be able to create new idea for problem solving related to

industry or societal issues.

L1, L2, L3,L4

3 Students will be to developentrepreneurial thinking with an idea to convert

project into product.

L1, L2, L3,L4,l5,L6

4 Students will be aware ofethics and plagiarism aspects in technical writing. L1, L2, L3,L4,l5,L6

Detailed Syllabus:

Module

No.

Topics Cognitive level attainment as

per revised Bloom Taxonomy

1 Research Publication L1, L2, L3,L4

Forming interest groups with mentors, Topic Identification, Literature Survey, and Sketching

of Idea/Design of Survey, Implementation, and Analysis of Results, Identifying journal

/conference for publication conference paper, Publishing of research Paper/Survey paper.

Evaluation by faculty as per format.

2 Management of Innovation and Technical Change L1, L2, L3,L4

What is innovation, kinds of Innovation, Innovation as a core business process, Developing an

innovation strategy, Sources of innovation, Creating new products and services

Idea competition and evaluation.

3 Research Ethics, IPR And Scholarly Publishing L1, L2, L3,L4,l5,L6

Ethical issues; IPR-intellectual property rights and patent law, commercialization, copy

right, royalty, trade related aspects of intellectual property rights (TRIPS); scholarly

publishing-IMRAD concept and design of research paper, citation and acknowledgement,

plagiarism, reproducibility and accountability.

Evaluation of product feasibility for IPR.

4 Entrepreneurship L1, L2, L3,L4,l5,L6

Concepts and practices of technology entrepreneurial thinking and entrepreneurship. Using

lectures, case studies, business plans, and student presentations, the course teaches

life skills in entrepreneurial thought and action that students can utilize in starting

technology companies or executing R&D projects in large companies.

Pitch presentationcompetition and evaluation

References:

Sr. No. Title Authors Publisher Edition Year

3. Research Methodology Methods and

Techniques

C.R. Kothari New Age

International

Limited,

2nd Edition 2004

4. Entrepreneurship Development and

Small Business Enterprise

Poornima M.

Charantimath

Pearson

Education

India

5thEdition 2005

3. Law Relating to Patents, Trade Marks,

Copyright, Designs and Geographical

Indications

B. L. Wadehra Universal

Law

Publishing

Co Ltd

Kindle 2004

Online References:

Sr. No. Website Name URL Modules

Covered

1. https://www.statpac.com https://www.statpac.com/online-software-manual/Basic-Research-

Concepts.htm

M1

2. https://www.slideshare.ne

t

https://www.slideshare.net/25Mksp/management-technology-innovation-

change

M2

3. https://www.eng.ufl.edu https://www.eng.ufl.edu/leadership/wp-

content/uploads/sites/7/2015/02/Engineering-Entrepreneurship-Course-

Overview.pdf

M4

4. 1

.

https://www.vesalius.edu https://www.vesalius.edu/wp-content/uploads/2016/11/BUS213G-S15.pdf

M3

new b.e. semester vii · 2019. 12. 30. · term work (25) total theory tutorial practical contact...

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